TNF-α Promoter Polymorphisms Predict the Response to Etanercept More Powerfully than that to Infliximab/Adalimumab in Spondyloarthritis

Rs1800629 polymorphism in TNF-alpha is associated with the susceptibility and initial short-term glucocorticoids efficacy in myasthenia gravis patients

Tumor necrosis factor-alpha (TNF-α) is a potent pro-inflammatory agent involved in various autoimmune and inflammatory diseases including myasthenia gravis (MG). In this study, we enrolled 409 adult MG patients and 487 healthy individuals to investigate the association between TNF-α polymorphism and MG. We found the rs1800629 A allele frequency was significantly higher in the MG group than in the control group. Subgroup analysis revealed that the A allele frequencies were significantly higher in the early-onset subgroup, non-thymoma subgroup, ocular-onset subgroup, and mild severity subgroup than in the control group. To minimize the interactions between clinical features, we used a comprehensive classification and found that the rs1800629 A allele frequency was significantly higher in the non-thymoma AChR-Ab negative subgroup than in the control group. In the analysis of initial short-term glucocorticoids (GC) efficacy in the treatment-naive patients, the rs1800629 A allele frequency was significantly higher in the unresponsive subgroup than in the responsive group and the control group. Logistic regression demonstrated the rs1800629 genotypes in the dominant model and disease duration prior to GC treatment independently contributed to initial short-term GC efficacy. In conclusion, our study revealed that in Chinese adult MG patients, rs1800629 polymorphism in TNF-α was associated with the susceptibility of MG and might indicate the initial short-term GC efficacy.

TNFα rs1800629 Polymorphism and Response to Anti-TNFα Treatment in Behçet Syndrome: Data from an Italian Cohort Study

Tumor Necrosis Factor-alpha (TNFα) rs1800629 (-308G>A) is a single nucleotide polymorphism (SNP) related to variable responses to anti-TNFα therapy. This therapy is efficient in severe and refractory manifestation of Behçet syndrome (BS), an auto-inflammatory systemic vasculitis. We investigated (1) the association between rs1800629 genotypes and responses to therapy and (2) the correlation between SNP and clinical patterns in a cohort of 74 BS Italian patients receiving anti-TNFα therapy with a follow-up of at least 12 months. The rs1800629 was genotyped through amplification, direct sequencing and bioinformatics analyses. The rs1800629 GG and GA genotypes were assessed as predictors of outcomes dividing the patients between therapy responders and non-responders. The rs1800629 GG and GA genotypes were found, respectively, in 59/74 (79.7%) and 15/74 BS patients (21.3%) (p < 0.05). We identified 16/74 (21.9%) non-responder patients, of which 9/16 (56.3%) showed the GG genotype and 7/16 (43.7%) the GA genotype. A total of 50/58 (86.2%) responder patients showed the GG genotype, and 8/58 (13.8%) the GA genotype (p < 0.05). The percentage of non-responder females (68.8%) was significantly higher than non-responder males (31.2%) (p < 0.05). No correlation between SNP and clinical patterns was observed. To successfully include rs1800629 as a predictive biomarker of TNFα inhibitor response, genome-wide association studies in larger, well-characterised cohorts are required.

Tumor Necrosis Factor-Alpha (+489 G/A) Polymorphism Can Predict the Response to Adalimumab in Chinese Han Patients With Ankylosing Spondylitis

BACKGROUND

Studies investigating the association between single nucleotide polymorphisms (SNPs) of tumor necrosis factor-alpha (TNFα) and the efficacy of adalimumab (ADA) in ankylosing spondylitis (AS) therapy have reported conflicting results. We aimed to investigate the value of SNP typing of TNFα in predicting the efficacy of ADA in AS.

MATERIALS AND METHODS

Eighty patients with active AS who received ADA treatment were followed up for 24 weeks. Six known SNPs of TNFα (+489G/A, -238G/A, -308G/A, -857C/T, -863C/A, and -1031C/T) were subjected to the SNaPshot SNP typing method, which has been proven to be a reliable, efficient, and cost-effective method for detecting SNPs. The relationship between each SNP genotype and the therapeutic efficacy of ADA was analyzed.

RESULTS

At the end of the 24-week follow-up, 58.8% of the patients with AS achieved Assessment of SpondyloArthritis International Society (ASAS) partial remission (PR), 67.5% of the patients achieved the criteria of an ASAS40 response (40% improvement on indices), and 53.8% of the patients achieved Ankylosing Spondylitis Disease Activity Score (ASDAS) major improvement (MI). The univariate analysis showed that patients with AS carrying the TNFα +489 A allele were more likely to achieve ASAS-PR, ASAS40 response criteria, and ASDAS-MI after ADA treatment. In the multivariate regression analysis, the TNFα +489 A allele was an independent factor influencing the efficacy of ADA in treating AS (ASAS-PR odds ratio (OR) = 2.66, 95% confidence interval (CI) = 1.01-7.01; ASAS40 OR = 4.56, 95% CI = 1.39-15.00; ASDAS-MI OR = 3.31, 95% CI = 1.02-10.69).

CONCLUSIONS

The patients carrying the TNFα +489 A allele may be more likely to experience better therapeutic efficacy and achieve the treatment target (ASAS-PR, ASAS40 response, or ASDAS-MI) after receiving ADA treatment. Detection of TNFα +489 G/A may predict the therapeutic efficacy of ADA, which can be used in clinical practice to tailor treatment for individual patients with AS. Further studies with larger sample sizes and longer follow-up periods with imaging evaluation are needed to verify our findings.

Genome-wide association analysis of anti-TNF-α treatment response in Chinese patients with psoriasis

Background: TNF-α inhibitors are effective biological agents for treating psoriasis, but the treatment responses differ across patients. This study aimed to identify genetic biomarkers of anti-TNF-α response in Chinese psoriasis patients using a genome-wide association approach.

Methods: We recruited two independent cohorts of Chinese psoriasis patients administered etanercept biosimilar (with or without methotrexate). We identified 61 and 87 good responders (PASI improvement ≥75%), 19 and 10 poor responders (PASI improvement <50%) after 24 weeks treatment in the two cohorts, respectively. Then we performed genome-wide association studies (GWAS) on anti-TNF-α response in each cohort independently, followed by a fixed-effects inverse-variance meta-analysis in the 148 good and 29 poor responders.

Results: We tested genetic associations with >3 million genetic variants in either cohort. Meta-analysis identified significant associations within seven loci at p < 10⁻⁵, which also showed consistent association evidence in the two cohorts. These seven loci include rs2431355 (OR = 6.65, p = 4.46 × 10⁻⁷, IQGAP2-F2RL2 on 5q13.3), rs11801616 (OR = 0.11, p = 1.75 × 10⁻⁶, SDC3 on 1p35.2), rs3754679 (OR = 0.17, p = 7.71 × 10⁻⁶, CNOT11 on 2q11.2), rs13166823 (OR = 0.09, p = 3.71 × 10⁻⁶, IRF1-AS1 on 5q31.1), rs10220768 (OR = 5.49, p = 1.48 × 10⁻⁶, NPAP1 on 15q11.2), rs4796752 (OR = 5.56, p = 1.49 × 10⁻⁶, KRT31 on 17q21.2), and rs13045590 (OR = 0.08, p = 9.67 × 10⁻⁷, CTSZ on 20q13.3). Of the seven SNPs, six SNPs showed significant eQTL effect (p < 1 × 10⁻⁶) for several genes in multiple tissues.

Conclusion: These results suggest novel biological mechanisms and potential biomarkers for the response to anti-TNF therapies. These findings warrant further validation.

Searching for New Genetic Biomarkers of Axial Spondyloarthritis

Background: Axial spondyloarthritis (axSpA) is a chronic inflammatory condition of the spine. In addition to musculoskeletal symptoms, there are also extra-articular manifestations. The aim of this study was to search for new biomarkers associated with the clinical presentation and treatment response in axSpA patients. Methods: In this study, 106 axSpA patients and 110 healthy controls were enrolled. Six single-nucleotide polymorphisms (SNPs) were selected for genotyping: ERAP1 rs2287987, ERAP2 rs2549782, TNF rs1800629, TNFRSF1A rs767455, TNFRSF1B rs1061622, and FCGR2A rs1801274. Participants were examined at baseline and after 12 and 24 weeks of anti-TNF therapy. Results: SNPs associated with high axSpA initial activity were TNFRSF1A rs767455 and TNFRSF1B rs1061622 (p < 0.008). The ERAP1 rs2287987 AA genotype was more frequently observed in patients with enthesitis (AA vs. G+, p = 0.049), while the TNFRSF1B rs1061622 GG genotype was more common in participants with uveitis (GG vs. TT, p = 0.042). Potential in predicting anti-TNF treatment response was demonstrated by ERAP1 rs2287987, ERAP2 rs2549782, TNFRSF1B rs1061622, and FCGR2A rs1801274. Conclusions: SNPs can be used to identify patients at risk of severe disease to initiate treatment earlier. Genetic testing will allow clinicians to choose the right drug for the patient.

The Associations of rs1799724 and rs361525 With the Risk of Ankylosing Spondylitis Are Dependent on HLA-B27 Status in a Chinese Han Population

Objectives

Human leucocyte antigen B27 (HLA-B27) is an important biomarker for ankylosing spondylitis (AS). However, delay in the diagnosis of AS is still common in clinical practice. Several single nucleotide polymorphisms (SNPs) in the coding gene of tumor necrosis factor alpha (TNFα) have been reported to be AS susceptibility loci. Our aim was to explore whether SNPs in TNFα could be used to improve the performance of HLA-B27 for predicting AS.

Methods

Five SNPs (rs1799964, rs1800630, rs1799724, rs1800629, and rs361525) spanning TNFα were genotyped by qPCR-Invader assay in 93 AS patients and 107 healthy controls for association analysis and linkage disequilibrium (LD) analysis. Random forest algorithm was utilized to construct the predictive classifiers for AS. HLA-B was genotyped by PCR-sequence-based typing in a subset of the HLA-B27-positive subjects (38 AS patients and 5 healthy controls).

Results

The T allele of rs1799724 was verified to significantly increase the risk of AS (OR = 4.583, p < 0.0001), while the A allele of rs361525 showed an association with the reduced AS risk (OR = 0.168, p = 0.009). In addition, the rs1799964^T-rs1800630^C-rs1799724^T-rs1800629^G-rs361525^G haplotype was significantly associated with a higher risk of AS (p < 0.0001). The optimal set of variables for classifiers to predict AS only consisted of HLA-B27. Strong associations with HLA-B27 status were found in both rs1799724 (p < 0.0001) and rs361525 (p = 0.001), and all the analyzed HLA-B27-positive subjects carried HLA-B*27:04 or HLA-B*27:05.

Conclusion

In the Chinese Han population, the minor allele T of rs1799724 could increase the risk of AS, while the minor allele A of rs361525 protects individuals from AS. However, the contributions of rs1799724 and rs361525 to AS risk were dependent on HLA-B27 status, suggesting the importance of taking the independence and specificity into consideration in AS susceptibility loci studies.

Precision Medicine: Towards Individualized Dosing in Pediatric Rheumatology

Despite an increase in the number of available therapeutics, many children with rheumatic disease continue to experience active inflammatory disease and treatment failure. One reason for treatment failure is the lack of dosing paradigms to account for the wide between-patient variability in drug pharmacokinetics because of developmental changes or genetic polymorphisms that effect drug absorption, distribution, metabolism, and elimination. This review highlights several strategies to optimize dosing for biologic and nonbiologic disease-modifying antirheumatic drugs, including therapeutic drug monitoring, pharmacogenomics, and the use of pharmacokinetic/pharmacodynamic modeling.

Review of cancer cell resistance mechanisms to apoptosis and actual targeted therapies

The apoptosis pathway is a programmed cell death mechanism that is crucial for cellular and tissue homeostasis and organ development. There are three major caspase-dependent pathways of apoptosis that ultimately lead to DNA fragmentation. Cancerous cells are known to highly regulate the apoptotic pathway and its role in cancer hallmark acquisition has been discussed over the past decades. Numerous mutations in cancer cell types have been reported to be implicated in chemoresistance and treatment outcome. In this review, we summarize the mutations of the caspase-dependant apoptotic pathways that are the source of cancer development and the targeted therapies currently available or in trial.

Novel approaches to develop biomarkers predicting treatment responses to TNF-blockers

Introduction: Chronic inflammatory diseases (CIDs) cause significant morbidity and are a considerable burden for the patients in terms of pain, impaired function, and diminished quality of life. Important progress in CID treatment has been obtained with biological therapies, such as tumor-necrosis-factor blockers. However, more than a third of the patients fail to respond to these inhibitors and are exposed to the side effects of treatment, without the benefits. Therefore, there is a strong interest in developing tools to predict response of patients to biologics. Areas covered: The authors searched PubMed for recent studies on biomarkers for disease assessment and prediction of therapeutic responses, focusing on the effect of TNF blockers on immune responses in spondyloarthritis (SpA), and other CID, in particular rheumatoid arthritis and inflammatory bowel disease. Conclusions will be drawn about the possible development of predictive biomarkers for response to treatment. Expert opinion: No validated biomarker is currently available to predict treatment response in CID. New insight could be generated through the development of new bioinformatic modeling approaches to combine multidimensional biomarkers that explain the different genetic, immunological and environmental determinants of therapeutic responses.

Harnessing Tumor Necrosis Factor Alpha to Achieve Effective Cancer Immunotherapy

Tumor necrosis factor alpha (TNFα) is a pleiotropic cytokine known to have contradictory roles in oncoimmunology. Indeed, TNFα has a central role in the onset of the immune response, inducing both activation and the effector function of macrophages, dendritic cells, natural killer (NK) cells, and B and T lymphocytes. Within the tumor microenvironment, however, TNFα is one of the main mediators of cancer-related inflammation. It is involved in the recruitment and differentiation of immune suppressor cells, leading to evasion of tumor immune surveillance. These characteristics turn TNFα into an attractive target to overcome therapy resistance and tackle cancer. This review focuses on the diverse molecular mechanisms that place TNFα as a source of resistance to immunotherapy such as monoclonal antibodies against cancer cells or immune checkpoints and adoptive cell therapy. We also expose the benefits of TNFα blocking strategies in combination with immunotherapy to improve the antitumor effect and prevent or treat adverse immune-related effects.

Not your average joint: Towards precision medicine in psoriatic arthritis

Precision medicine, propelled by advances in multi-omics methods and analytics, aims to revolutionize patient care by using clinically-actionable molecular markers to guide diagnostic and therapeutic decisions. We describe the applications of precision medicine in risk stratification, drug selection, and treatment response prediction in psoriatic arthritis, for which targeted, personalized approaches are steadily emerging.

Tumor Necrosis Factor α Blockade: An Opportunity to Tackle Breast Cancer

Breast cancer is the most frequently diagnosed cancer and the principal cause of mortality by malignancy in women and represents a main problem for public health worldwide. Tumor necrosis factor α (TNFα) is a pro-inflammatory cytokine whose expression is increased in a variety of cancers. In particular, in breast cancer it correlates with augmented tumor cell proliferation, higher malignancy grade, increased occurrence of metastasis and general poor prognosis for the patient. These characteristics highlight TNFα as an attractive therapeutic target, and consequently, the study of soluble and transmembrane TNFα effects and its receptors in breast cancer is an area of active research. In this review we summarize the recent findings on TNFα participation in luminal, HER2-positive and triple negative breast cancer progression and metastasis. Also, we describe TNFα role in immune response against tumors and in chemotherapy, hormone therapy, HER2-targeted therapy and anti-immune checkpoint therapy resistance in breast cancer. Furthermore, we discuss the use of TNFα blocking strategies as potential therapies and their clinical relevance for breast cancer. These TNFα blocking agents have long been used in the clinical setting to treat inflammatory and autoimmune diseases. TNFα blockade can be achieved by monoclonal antibodies (such as infliximab, adalimumab, etc.), fusion proteins (etanercept) and dominant negative proteins (INB03). Here we address the different effects of each compound and also analyze the use of potential biomarkers in the selection of patients who would benefit from a combination of TNFα blocking agents with HER2-targeted treatments to prevent or overcome therapy resistance in breast cancer.

Machine Learning to Predict Anti-Tumor Necrosis Factor Drug Responses of Rheumatoid Arthritis Patients by Integrating Clinical and Genetic Markers

OBJECTIVE

Accurate prediction of treatment responses in rheumatoid arthritis (RA) patients can provide valuable information on effective drug selection. Anti-tumor necrosis factor (anti-TNF) drugs are an important second-line treatment after methotrexate, the classic first-line treatment for RA. However, patient heterogeneity hinders identification of predictive biomarkers and accurate modeling of anti-TNF drug responses. This study was undertaken to investigate the usefulness of machine learning to assist in developing predictive models for treatment response.

METHODS

Using data on patient demographics, baseline disease assessment, treatment, and single-nucleotide polymorphism (SNP) array from the Dialogue on Reverse Engineering Assessment and Methods (DREAM): Rheumatoid Arthritis Responder Challenge, we created a Gaussian process regression model to predict changes in the Disease Activity Score in 28 joints (DAS28) for the patients and to classify them into either the responder or the nonresponder group. This model was developed and cross-validated using data from 1,892 RA patients. It was evaluated using an independent data set from 680 patients. We examined the effectiveness of the similarity modeling and the contribution of individual features.

RESULTS

In the cross-validation tests, our method predicted changes in DAS28 (ΔDAS28), with a correlation coefficient of 0.405. It correctly classified responses from 78% of patients. In the independent test, this method achieved a Pearson's correlation coefficient of 0.393 in predicting ΔDAS28. Gaussian process regression effectively remapped the feature space and identified subpopulations that do not respond well to anti-TNF treatments. Genetic SNP biomarkers showed small contributions in the prediction when added to the clinical models. This was the best-performing model in the DREAM Challenge.

CONCLUSION

The model described here shows promise in guiding treatment decisions in clinical practice, based primarily on clinical profiles with additional genetic information.

IgG Galactosylation status combined with MYOM2-rs2294066 precisely predicts anti-TNF response in ankylosing spondylitis

Background

Tumor necrosis factor (TNF) blockers have a high efficacy in treating Ankylosing Spondylitis (AS), yet up to 40% of AS patients show poor or even no response to this treatment. In this paper, we aim to build an approach to predict the response prior to clinical treatment.

Methods

AS patients during the active progression were included and treated with TNF blocker for 3 months. Patients who do not fulfill ASASAS40 were considered as poor responders. The Immunoglobulin G galactosylation (IgG-Gal) ratio representing the quantity of IgG galactosylation was calculated and candidate single nucleotide polymorphisms (SNPs) in patients treated with etanercept was obtained. Machine-learning models and cross-validation were conducted to predict responsiveness.

Results

Both IgG-Gal ratio at each time point and differential IgG-Gal ratios between week 0 and weeks 2, 4, 8, 12 showed significant difference between responders and poor-responders. Area under curve (AUC) of the IgG-Gal ratio prediction model was 0.8 after cross-validation, significantly higher than current clinical indexes (C-reactive protein (CRP) = 0.65, erythrocyte sedimentation rate (ESR) = 0.59). The SNP MYOM2-rs2294066 was found to be significantly associated with responsiveness of etanercept treatment. A three-stage approach consisting of baseline IgG-Gal ratio, differential IgG-Gal ratio in 2 weeks, and rs2294066 genotype demonstrated the ability to precisely predict the response of anti-TNF therapy (100% for poor-responders, 98% for responders).

Conclusions

Combination of different omics can more precisely to predict the response of TNF blocker and it is potential to be applied clinically in the future.

Electronic supplementary material

The online version of this article (10.1186/s10020-019-0093-2) contains supplementary material, which is available to authorized users.

Genetics and Functional Genomics of Spondyloarthritis

Spondyloarthritis (SpA) is a chronic inflammatory disorder with high heritability but with complex genetics. It encompasses several entities that share common clinical features. Most of the genetic studies in SpA have been restricted to ankylosing spondylitis (AS), the prototypical form of SpA. However, there is growing evidence of shared genetic background between all the SpA subtypes and also with some other immune-mediated diseases. The most important part of SpA heritability comes from the HLA-B27 allele in the major histocompatibility complex (MHC) that explains around 25% of the attributable heredity. Several other loci outside of the MHC have been shown to be involved in the disease. However, all these non-MHC loci explain only a small additional fraction of disease predisposition. Thus, a substantial fraction of SpA genetic basis remains poorly understood. Gene expression profiling is a complementary approach to elucidate the underlying mechanisms and pathways that drive the disease. Several expression profiling studies have been undertaken in SpA. However, results have been quite disappointing with little overlap between the studies largely due to the small sample sizes, resulting in limited power to discover small effects. In this review, we summarize current knowledge on genetic findings concerning SpA and we describe strategic approaches for identification of additional variants, with a focus on rare variants in familial forms. We also provide an overview of gene expression studies in SpA and discuss the possibilities offered by high-throughput RNA sequencing technologies, in particular in sorted cells. Finally, issues in establishing molecular mechanisms underlying genetic association hits and potential translational applications will be addressed.

Genetics in TNF-TNFR pathway: A complex network causing spondyloarthritis and conditioning response to anti-TNFα therapy

Objectives

We investigated whether polymorphisms (SNPs) in the promoter region of TNFA, or in the autoinflammatory TNFRSF1A and MEFV genes, concur with HLA-B27 in enhancing the risk of Spondyloarthritis (SpA) and/or in predicting the response to anti-TNFα treatment.

Methods

373 controls and 137 SpA (82 with Psoriatic Arthritis-PsA and 55 with Ankylosing Spondylitis- AS; 98/137 under TNFα inhibitor therapy) from the Veneto Region (Italy) were studied. TNFA polymorphisms (-1031T>C;-857C>T;-376G>A;-308G>A;-238G>A) and HLA-B27 were assayed by RT-PCR. Direct sequencing of MEFV (exons 2,3,5 and 10) and TNFRSF1A (exons 2,3,4 and 6) genes were performed.

Results

HLA-B27 was associated with AS (χ² = 120.1; p = 0.000). Only the TNFA -1031T>C was singly associated with SpA, and the haplotype C/G, resulting from -1031T>C/-308G>A combination, was significantly associated with a reduced risk of SpA (OR: 0.67, CI: 0.46–0.97; p = 0.035). Two SNPs were identified in TNFRSF1A, the R92Q (Minor allele frequency-MAF = 0.034) and c.625+10A>G (MAF = 0.479). None of them was associated with SpA (p>0.05). The TNFRSF1A c.625+10 G allele was associated with late response to anti-TNFα therapy (p = 0.031). Twenty-one SNPs were identified in MEFV gene, 10 with a known potential functional significance. Variant alleles were extremely rare in our population (MAF<0.025) except for R202Q (MAF = 0.27). None was associated with SpA diagnosis (p>0.05).

Conclusion

TNFRSF1A and MEFV gene SNPs are not associated with SpA in the North-East of Italy. AS risk appears to depend not only on HLA-B27, but also on the protective TNFA haplotype -1031C/-308G. The TNFRSF1A c.625+10A>G impacts on the response to anti-TNFα therapy.

Age determines response to anti-TNFα treatment in patients with ankylosing spondylitis and is related to TNFα-producing CD8 cells

Younger age is a predictor of good clinical response to treatment with tumour necrosis factor (TNF) α inhibitors in ankylosing spondylitis (AS) patients; therefore, the aim of the study was to determine age-related differences in cellular functions, which can predict the response. High disease activity AS patients were treated with TNFα inhibitors for 12 weeks. Based on the percentage of Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) improvement, patients were divided into responding or non-responding groups. Cytometric and clinical assessment were determined at baseline, 4, and 12 weeks after initiation of anti-TNFα treatment. Expression of activation markers on T cells and intracellular cytokine staining was performed. Baseline percentage of TNFα-producing CD8 cells was lower in responders than in non-responders (20.8 ± 2.9 vs 40.7 ± 8.2; P = 0.04 in T test) and increased in the responding group during the first month of treatment (20.8 ± 2.9 vs 30.3 ± 2.5; P = 0.02). Moreover, its baseline level correlated with age (r = 0.7; P = 0.0009) but not with BASDAI improvement adjusted for age. There were no differences in the baseline percentage of IL-4, IL-17A, and IFNγ within CD4 and CD8 cells nor in the expression of CD25, CD28, and CD69 on these cells between responders and non-responders. However, baseline level of CD4+CD28null cells correlated with the percentage of BASDAI improvement while analysed as a continuous variable adjusted for age (r = − 0.4; P = 0.048). Clinical predictors of response were also determined. Influence of age on the response to anti-TNFα treatment in AS patients could be mediated by TNFα-producing CD8 cells.

Polymorphisms associated with etanercept response in moderate-to-severe plaque psoriasis

AIM

Few studies have evaluated the influence of pharmacogenetics in psoriatic patients treated with etanercept.

MATERIALS & METHODS

We evaluated the association between 124 polymorphisms with the response to etanercept in patients with moderate-to-severe plaque psoriasis at 3 months (n = 78) and 6 months of treatment (n = 68).

RESULTS

The results of the multivariate analysis showed an association between polymorphisms rs13437088 (HLA-B/MICA), rs96844 (MAP3K1), rs2431697 (PTTG1), rs9304742 (ZNF816A) and the response to etanercept at 3 months. Besides polymorphisms rs928655 (GBP6) and rs2546890 (IL12B) were associated to response at 6 months.

CONCLUSIONS

Nevertheless, these biomarkers should be validated in large-scale studies before its implementation in clinical practice.